University of Groningen
Influence of sheep manure addition on biogas potential and methanogenic communities
during cow dung digestion under mesophilic conditions
Achinas, Spyridon; Li, Yu; Achinas, Vasileios ; Euverink, Gerrit Jan Willem
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Sustainable Environment Research
DOI:
10.1016/j.serj.2018.03.003
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Achinas, S., Li, Y., Achinas, V., & Euverink, G. J. W. (2018). Influence of sheep manure addition on biogas
potential and methanogenic communities during cow dung digestion under mesophilic conditions.
Sustainable Environment Research, 28(5), 240-246. https://doi.org/10.1016/j.serj.2018.03.003
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Original Research Article
In
fluence of sheep manure addition on biogas potential and
methanogenic communities during cow dung digestion under
mesophilic conditions
Spyridon Achinas
a,*, Yu Li
a, Vasileios Achinas
b, Gerrit Jan Willem Euverink
aaFaculty of Science and Engineering, University of Groningen, Groningen 9747 AG, The Netherlands bUnion of Agricultural Co-operatives of Monofatsi, Heraklion 70016, Greece
a r t i c l e i n f o
Article history:
Received 31 October 2017 Received in revised form 25 January 2018 Accepted 15 March 2018 Available online 22 March 2018 Keywords: Anaerobic co-digestion Animal slurries Biogas potential Methanogens
a b s t r a c t
The efficient treatment of animal slurries can support the bioenergy management and environmental protection; however, the low biogas yield and quality are the major constraints. The object of this paper is to investigate how the co-digestion of sheep manure and cow dung by not using inoculum influences the performance of the process and determine the methanogenic communities at the end of the experiment. Biochemical Methane Potential essays were conducted in mesophilic conditions in order to determine the biogas-methane potential. Enhanced biogas production was achieved from the mono-digestion of cow dung with 104.3 NmL biogas g1VS and the co-digestion of cow dung and sterilized sheep manure with a lower biogas yield of 89.0 NmL biogas g1VS.
© 2018 Chinese Institute of Environmental Engineering, Taiwan. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
Dairy industry is now a significant global industry and it con-tributes to nearly 7% of total agricultural production value[1]. It is also one of the most important industries in the Netherlands. With the expansion of the big farms, a lot of herds now lead to large amount of livestock manure which causes serious environmental problems such as greenhouse gas (GHG) emissions, surface water contamination, and animal related pathogens[2,3]. Among live-stock manure, the majority is produced by cattle. As ruminants (mainly dairy and beef cattle) contribute the largest proportion (61%) to livestock-related GHG emissions[4,5], there is an increased pressure to reduce their carbon footprint.
Anaerobic digestion (AD) produces biogas for heat and power as well as solid residue - so-called digestate-which can also be used as organic fertilizer in agricultural activities[6]. The basic steps of the organic mass conversion to biogas are illustrated in Fig. 1. The mono-digestion of cattle manure is proved to be reasonable because it contains bacteria needed in the fermentation phase as well as degradable materials such as carbohydrate and lips. But on
the other hand, the fermentation of cattle manure alone often re-sults in low biogas production and sometimes reaches only quarter of the theoretical biogas yield. Moreover, compared with other farm animals, the biogas yield of cattle is lower because of its lignin complexes from fodder that are very resistant to AD[7]. It is critical tofind another proper substrate to co-digestion with cattle manure in order to balance the nutrition and dilute the limitations in the AD process.
This paper chooses sheep manure (SM) for co-digestion with cow dung (CD). Cestonaro et al.[8]previously used the co-digestion of sheep bedding with cow manure without inoculum at room temperature and found that when adding 50% or more cow manure, it would increase the biogas production and improves the digestate quality. Alvarez and Liden[9]used the co-digestion of llama, cow manure and SM for improving methane production and found that co-digestion was better than the mono-digestion among those kinds of animal manure. However, previous studies of cow manure co-digestion with SM do not take into account the AD without inoculum. So there is a need to see the performance of co-digestion of sheep and cow manure without inoculum in order to investigate the interactions of the microorganisms present in the animal slurries. The object of this paper is to investigate how the co-digestion of SM and CD by not using inoculum influences the performance of the process and determine the methanogenic communities at the end of the experiment.
* Corresponding author.
E-mail address:s.achinas@rug.nl(S. Achinas).
Peer review under responsibility of Chinese Institute of Environmental Engineering.
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https://doi.org/10.1016/j.serj.2018.03.003
2468-2039/© 2018 Chinese Institute of Environmental Engineering, Taiwan. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
2. Materials and methods
2.1. Origin of inoculum and substrates
Animal slurries were used as substrates in the experiments. Fresh CD and SM were collected from a farm in Groningen (Netherlands). Two different materials were selected for experi-mental essays as they are considering important source for agri-cultural bioenergy production. Two additional samples of cow manure and SM were undergone autoclaving (10 min) in order to eliminate the microorganisms. Pecorini et al.[10]report that short-term autoclaving does not influence the hydrolysis of cellulosic fraction of non-biodegradable substances. Their characteristics in terms of volatile solids (VS), total solids (TS) and chemical oxygen demand (COD) are given in Table 1. All the substrates were
undergone agitating for 5 min beforefinal feed in order to increase the active surface of the particles. The substrates were stored at 4C prior to use.
2.2. Experimental essays
The experiment carried out in batch mode using the water displacement method for measuring the biogas produced. The biogas potential was based on the total volume of biogas produced during the degradation period and is defined as NmL biogas g1VS
added.Fig. 2represents the set-up employed for the experimental procedure. In our set-up, 500 mL serum bottles were used for the essays (Fig. 2), flushed with N2 for 2 min in order to maintain
anaerobic conditions, placed in an incubator at a constant meso-philic temperature (36± 1C) and shaken at 150 rpm during the
experimental period of the assay. Two tests studied with CD and SM digestion, the other three tests studied mixtures of CD:SM, CD:SSM (sterilized sheep manure) and SCD:SM with ratio 1:1 based on VS concentrations. Stocks samples (substrates solutions) were pre-pared and the serum bottles were filled starting with the sub-strates, followed by the addition of distilled water in order to achieve a working volume of 350 mL. No inoculum or additional external nutrients/trace elements was added to the serum bottles. The experimental conditions and the content of the reactors are given inTable 2.
Fig. 1. Steps related with anaerobic digestion of organic materials.
Table 1
Characteristics of the substrates.
Feedstocks* TS (g kg1) VS (g kg1) COD (g kg1) TS/VS COD/VS
Cow dung (CD) 121.3 107.2 134.7 1.1 1.3 Sheep manure (SM) 252.8 213.8 349.2 1.1 1.5 Sterilized cow dung (SCD) 135.4 121.7 186.6 1.2 1.6 Sterilized sheep manure (SSM) 237.4 199.0 250.2 1.2 1.3
The daily data of the biogas volume were normalized to normal millilitre (NmL) (dry gas, T¼ 0C, P¼ 760 mm Hg ¼ 100 kPa)
ac-cording to the equation[11]:
VN¼ ðV 273 ð760 pwÞÞ=ðð273 þ TÞ 760Þ
where VNis the volume of the dry biogas at standard temperature
and pressure (NmL), V ¼ recorded volume of the biogas (mL), pw¼ water vapor pressure as a function of ambient temperature
(mm Hg), and T¼ ambient temperature (K).
All the experiments were carried out in triplicate and the results were expressed as means. The biogas measuring devices are simple water displacement bottles. The test ended when no more signi fi-cant biogas production was observed, meaning no water noticed. The data analysis was conducted using Microsoft Excel. The daily data of the biogas volume were normalized to normal mL (dry gas, T¼ 0C, P¼ 101.3 kPa). Biogas composition was determined at the
end of the experimental period by using a micro-GC device and the methane potential was also expressed as NmL methane per gr of VS (ml CH4g1VS).
2.3. Analytical methods
TS and VS contents determined according to Standard Method 1684[12]. Total alkalinity (TA) and total volatile fatty acids (TVFA) were measured according to the standard protocol EPA-430/9-77-006/March1977. COD was calculated using a test kit (Hach Lange GmbH) according to the manufacturer's instructions and a
spectrophotometer (DR/2010, Hach). A pH meter (HI991001, Hanna Instruments) was used to measure the pH. The biogas production was determined by means of water volume displacement. The concentrations of CH4 and CO2 were quantified by a micro gas
chromatograph (single channel 2-stream selector system, Thermo Fisher Scientific equipped with a chromatographic column (PLOT-U) with Helium as carrier gas at a totalflow of 10 mL min1. A gas standard consisting of 50% (v/v) CH4, 20% (v/v) CO2and 30% (v/v) N2
was used for calibrating gas chromatographic results. All the results represent the mean value of experiments conducted in triplicate with an accuracy of 10%.
2.4. Microbiological method DNA extraction and quantitative real time polymerase chain reaction (qPCR) analyses
Samples of 5 mL (from the first and last day) were frozen at20C until DNA extraction was conducted. DNA was isolated
from the samples using the FastDNA SPIN Kit for soil (MP Bio-medicals) according to the protocol provided by the manufacturer
[13]. DNA was stored20C after the isolation until qPCR method
was performed using one mL of extracted DNA samples. DNA was eluted in 500
m
L milli-Q water. Eight primer sets (Table 3) were used for isolation of the 16S rRNA gene sequences of the following microorganisms: the order of Methanobacteriales, Meth-anococcales and Methanomicrobiales, the families Meth-anosarcinaceae and Methanosaetaceae, as well as the total bacteria and archaea according to the experimental procedures followed by Yu et al.[14].qPCR was performed on DNA extracts of samples using iQ mastermix (Biorad)[15], Syto-9 as thefluorophore[16]at afinal concentration of 10
m
M and primers at a final concentration of 400 nM each. For the qPCR 5m
L of template, 5m
L primer mix, containing 1.6m
M forward primer and 1.6m
M reverse primer and 10m
L iQ mastermix containing Syto-9 were mixed into a sterile 96-wells plate using an automated liquid handler (BeckmaneCoulter Biomek 3000, Fullerton, CA, USA). All qPCR reactions were per-formed using an initial denaturation at 94C for 3 min, followed by 45 cycles of amplification with each cycle consisting of denatur-ation (30 s at 94C), annealing (30 s at 60C), elongation (30 s at 72C) and afluorescence measurement (5 s at 80C, excitation at450e490 nm, emission at 515e530 nm). This was followed by a final extension at 72C for 5 min qPCR reactions were performed
on an MJ Thermocycler PTC-200 with a Chromo 4 Detector (Biorad). For data analysis the software package MJ Opticon Monitor 3.1 was used with afixed threshold setting of 1.6.
Fig. 2. experimental set-up (a) serum bottles, (b)flasks-reactors.
Table 2
Experimental conditions of the batch tests. Particular Experimental design Exp. set Co-digestion
(based on VS) Organic load (g VSaddedL1) Mass of substrate (g) added in the 300 mL bottle Mass of co-substrate (g) added in the 300 mL bottle CD e 5 13.99 e SM e 5 7.02 e CD:SM 1 5 6.99 3.51 CD:SSM 1 5 6.99 3.77 SM:SCD 1 5 3.51 6.16 Table 3
Primers used in this study.
Primer Sequence 5’ / 3’/[Restriction Enzyme] Length
ARC787F ATTAGATACCCSBGTAGTCC 20 ARC1059R GCCATGCACCWCCTCT 16 BAC338F ACTCCTACGGGAGGCAG 17 BAC805R GACTACCAGGGTATCTAATCC 21 MCC495F TAAGGGCTGGGCAAGT 16 MCC832R CACCTAGTYCGCARAGTTTA 20 MBT857F CGWAGGGAAGCTGTTAAGT 19 MBT1196R TACCGTCGTCCACTCCTT 18 MMB282F ATCGRTACGGGTTGTGGG 18 MMB832R CACCTAACGCRCATHGTTTAC 21 MSL812F GTAAACGATRYTCGCTAGGT 20 MSL1159R GGTCCCCACAGWGTACC 17 Msc380F GAAACCGYGATAAGGGGA 18 Msc828R TAGCGARCATCGTTTACG 18 Mst702F TAATCCTYGARGGACCACCA 20 Mst862R CCTACGGCACCRACMAC 17
S. Achinas et al. / Sustainable Environment Research 28 (2018) 240e246 242
3. Results and discussion 3.1. Characterization of bioreactors
To estimate the removal percentage of COD and VS, measure-ments were performed at the beginning and at the end of the es-says. The characteristics of samples (start and end) in terms of VS, TS, COD, TA and TVFA are given inTable 4. The pH was stable which can be validated from the slight changes in TVFA. The COD and VS removal percentages are given inTable 5.
3.2. Potential biogas production
The biogas potential of two kinds of animal slurries was deter-mined without using inoculum. The product potential of the AD process was determined with respect to biogas and methane amounts (Table 6). Ideal anaerobic conditions as well as appro-priate microbial and enzymes availability were taken into account during the experimental design. The addition of SM influences the digestion of CD and hence the biogas production yield.
Fig. 3represents the cumulative biogas content of all digesters as function of time. CD had a better biogas yield reaching a total production of 52 NmL of biogas in 24 d which corresponds on 104 NmL biogas g1 VS added. The fact that the inoculum (anaerobic sludge) was not used is responsible for the long lag phase of biogas production. The lower biogas production of the mixture CD:SM could be due to antagonistic phenomena between the microor-ganisms of CD and SM.
Fig. 4 shows the daily biogas production of all reactors. The highest daily biogas production occurred in bioreactor with CD reaching a production peak of 10.2 NmL. InTable 6, biogas yields
and methane percentage are presented. The results clearly show the main contribution of the CD-based microorganisms on biogas production. The samples with SCD or without CD showed low biogas production potential. Data show that the most degradable is CD. A comparison between biogas yields and methane composi-tions for the 5 configurations is depicted inTable 6. Nevertheless, the quality of biogas (means percentage of methane) has to be considered. Among the five samples CD provided considerable better quality biogas reaching 64%.
3.3. Microbial community analysis
qPCR analysis was performed to determine the total population of bacteria and archaea as well as to characterize the different methanogenic communities in the five different flasks at the beginning and end of the experiment. Total bacteria copy numbers were similar in the reactors except in the case of CD-SM and SMþ SCD mixtures where it was a factor 10 lower. In general, total bacteria abundance was roughly a factor 10 higher at the beginning of the experiments. In the case of CD-SM and SM-SCD mixtures, total bacteria copy numbers were higher at the end (Fig. 5). A clear difference in methanogenic community composition and abun-dance was observed in digesters. Total archaea number shows an increasing trend during the experiment justifying the low biogas production (Fig. 3).
A majority of archaea was affiliated to Methanomicrobiales, and Mathanobacteriales and less to Methanosaetaceae and Meth-anosarcinaceae (Fig. 6). The Methanococcales abundance was below detection limit in all the samples. Also, it is noted that Methanosarcinaceae was found to increase in number in all the reactors when the experiment was ended. Methanomicrobiales, which was abundant in the beginning phase of SM-containing flasks, are reduced at the end indicating that methane production was limited. In theflasks with CD and CD-SSM the percentage of Methanobacteriales was increased indicating the higher biogas yields. The evaluation of the different methanogenic species revealed a clear view for co-digestion samples and most specifically for sheep addition. As for mono-digestion of SM, the total amount of Methanobacteriales in this treatment has a decreasing trend and reflects the lowest biogas, perhaps due to strong inhibition in mono-digestion of SM which hinders the growth of methanogens. The stable pH and TVFA values from the beginning and the end of the experiment (Table 4) indicate that higher amount of substrates can be treated. However, thesefindings cannot explain the direct correlation between the methanogenic communities and process conditions. The importance of co-substrate selection for biogas potential essays is important, as substrates contain specific mi-crobial species which is related to different metabolic pathways during the AD as influences between microorganisms occur. 4. Conclusions
These essays highlighted the potential of cow dung and SM conversion to biogas through AD. Exploring the interactions be-tween the different species of microorganisms in the samples and their effect into the conversion factor is necessary for further research. There are many different archaea endowed with an excellent capacity to produce methane, but for some unknown reasons, its exploration continues to be elusive. Problems con-nected with the use of SM are obvious from the low methane yield. We also need to explore alternative animal slurries which could be economically viable. From the experiment, it can be concluded that CD-based microorganisms make up the predominant factor for biogas production. The samples with CD, and CD-SM mixture resulted in 104 and 89 NmL biogas g1 VS respectively.
Pre-Table 4
Physical and biochemical properties of samples at the beginning and end of the experiment. Samples* pH TS (g L1) VS (g L1) COD (g L1) TA (mg CaCO3L1) TVFA (mg acetate L1) Start CD 7.25 7.1 1.6 145.0 240 524 SM 7.16 7.8 1.8 299.1 231 530 CD:SM 7.21 7.2 1.7 206.7 237 566 CD:SSM 7.18 7.3 1.8 220.2 231 511 SM:SCD 7.28 7.2 1.7 228.0 234 477 End CD 7.02 6.4 1.2 94.5 239 488 SM 7.19 6.8 1.6 244.8 231 478 CD:SM 7.23 6.3 1.5 146.5 240 483 CD:SSM 7.24 6.8 1.5 142.0 243 466 SM:SCD 7.26 7.0 1.5 189.0 238 485 Table 5
Removal percentages of VS and COD after 24 d.
Samples* VS (%) COD (%) CD 22± 2 35± 4 SM 10± 1 18± 3 CD:SM 15± 3 29± 4 CD:SSM 19± 4 36± 5 SM:SCD 9± 1 17± 3 Table 6
Biogas yield and percentage of methane in 24 d.
Samples Biogas yield (NmL biogas g1VS) Methane in biogas (%)
CD 104 64
SM 8 54
CD:SM 77 61
CD:SSM 89 59
SM:SCD 23 56
treatment can increase bio-methane production but economic evaluation is needed for these pre-treatments.
On the other hand, the samples containing SM-based microor-ganisms resulted in lower yields and the AD is probably inhibited from inactivity of the microorganisms. Compared with other pre-vious experiments using CM and SM as substrate, our research offers a new perspective to understand the biochemical in-teractions within during the process, as the manure from these two typical ruminant animals contains many microbes themselves and it is important tofigure out the microbial activities during the AD in order to have a better understanding of the whole process. Since AD is driven by several key microbes a good understanding of the
succession of these microbes may provide an answer to the correlating performance in practical application.
From the cumulative methane yield of different treatments, conclusion can also be drawn that thermal treatment used in this experiment can increase the methane yield of co-digestion CM and SM. Thus, thermal pretreatment may be an efficient way to treat manure waste in practical AD plants. Although there are several opportunities in the biogas sector, there are however challenges that cannot be ignored and barriers that have to be overcome. Considering the aforementioned facts, as well as the high avail-ability of agro waste, the use of CD and SM as substrates for AD represents an option for large-scale applications.
Fig. 3. BMP assay curves showing total biogas production (NmL) from 5 different samples. Error bars show standard deviations.
Fig. 4. BMP assay curves for a 24 d run showing daily biogas production (mL) from 5 different samples. S. Achinas et al. / Sustainable Environment Research 28 (2018) 240e246
Acknowledgements
The authors would like to thank the providers of the substrates. The authors also kindly thank the Engineering and Technology Institute of Groningen at the University of Groningen for the use of the facilities.
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Fig. 5. Real-time qPCR results in the different samples, showing the total bacteria (blue) and total archaea (red). Error bars show standard deviations.
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